Statistics Courses (07-08 Course Offerings Bulletin)

Note: A caret (^) denotes that the course will not be offered this year. An asterisk (*) indicates that the course is offered every other year.

133 Statistics for the Business Sciences U 5

Introduction to basic concepts of descriptive statistics and probability; including graphical and numerical data summaries, properties of discrete and continuous probability distributions, and sampling distributions.

Su, Au, Wi, Sp Qtrs. 3 hr lecture; 2 1-hr recitations. Night version 3 hr lecture (1.5-hr twice/week) + 1 2-hr recitation. H133 (honors) may be available to students enrolled in an honors program or by permission of dept or instructor. Prereq: Math 132 and CS&E 200.

135 Elementary Statistics U 5

Introduction to probability and statistics, experiments, and sampling, data analysis and interpretation.

Su, Au, Wi, Sp Qtrs. 3 1-hr cl, 2 labs. Prereq: Math 050 or Mathematics Placement Level S. Not open to students with credit for any of the following: 125, 145, 245, Econ 442, Ed-T&P 786, Mol Gen 650, Polit Sc 685, Psych 220 or 510, or Soc Work 570 or 571. GEC data analysis course.

145 Introduction to the Practice of Statistics U 5

Topics include probability, descriptive statistics, correlation, regression, design of experiments, sampling, estimation, and testing; emphasis on applications, statistical reasoning, and data analysis using statistical software.

Su, Au, Wi, Sp Qtrs. 3 1-hr cl, 2 labs. Prereq: Math placement level L or M, Math 116 or 130 or 148 or 150 or 151 or equiv. GEC data analysis course.

201 Statistics in Your World

Explore and learn more about popular real-world topics using statistics as your tools. Statistical techniques include contingency tables, regression, confidence intervals and hypothesis testing. Prereq: One GEC in statistics or equiv or permission of instructor. 201 decimals cannot be used to replace a Data Analysis GEC. Cannot repeat decimals.

201.01 Statistics in the Sports World U 3

Ask and answer questions, debate issues and analyze data from your favorite sports using statistics. Statistical techniques include contingency tables, regression, estimation, confidence levels, testing.

Au Qtr. 2 1.5-hr labs.

245 Introduction to Statistical Analysis U 5

Calculus-based introduction to data analysis, experimental design, sampling, probability, and inference.

Au Qtr. 3 cl, 2 1-hr labs. Prereq: Math 152 or equiv. GEC data analysis course.

H246 Intermediate Data Analysis U 4

Intermediate data analysis including multiple regression, analysis of variance, nonparametric methods, and time series. Emphasis on statistical reasoning and using statistical software.

Wi Qtr. 4 1-hr cl. Prereq: 245 (or credit for 245 based on AP Statistics exam score). Student must have honors or scholars standing.

420 Introduction to Mathematical Statistics I U 5

Basic concepts in mathematical statistics, including probability, discrete and continuous distributions and densities, mathematical expectation, functions of random variables, transformation techniques, sampling distributions, order statistics.

Prereq: Math 254 or permission of instructor. Not open to students with credit for 520, 610, or 620.

421 Introduction to Mathematical Statistics II U 5

Calculation and evaluation of point estimators, interval estimation, Neyman- Pearson lemma, uniformly most powerful tests, likelihood ratio tests, chi-square, F, and nonparametric tests.

Prereq: 420. Not open to students with credit for 521 or 621.

427 Introduction to Probability and Statistics for Engineering and the Sciences I U 3

Introduction to probability, discrete and continuous random variables, expected value, and sampling distributions.

Su, Au, Wi, Sp Qtrs. 3 cl. Prereq: Math 153 or 254 or permission of instructor. This course is not intended to stand alone as an introduction to probability and statistics. It should be followed by 428. GEC data analysis course.

428 Introduction to Probability and Statistics for Engineering and the Sciences II U 3

Continuation of 427; point and interval estimation; hypotheses tests for proportions, means, variances, and goodness-of-fit; least squares regression.

Su, Au, Wi, Sp Qtrs. 3 cl. Prereq: 427. Not open to students with credit for 426.

451 Statistical Foundations of Survey Research U 5

Study objectives; survey and sampling design, implementation, ethics. Statistical analysis of survey data including confidence intervals, hypothesis tests and model building. Interpretation, communication of results.

Au Qtr. 3 80-min sessions. Prereq: One introductory course in data analysis (such as Stat 135), and college algebra (Math 104 or equiv). Not open to students with credit for 651.

494 Group Studies U 3-5

Designed to give groups of students an opportunity to pursue special studies not otherwise offered.

Su, Au, Wi, Sp Qtrs. Prereq: Permission of instructor. Repeatable to a maximum of 10 cr hrs.

520^ Mathematical Statistics I U G 5

Probability, random variables, discrete and continuous distributions; binomial, Poisson, normal, gamma (chi-square), t, F, distributions; change of variable and moment-generating function techniques; order statistics; limit theorems.

Au Qtr. 5 cl. Prereq: Math 254 or written permission of instructor. Not open to students with credit for 610 or 620. GEC data analysis course.

521^ Mathematical Statistics II U G 5

Confidence intervals; minimum variance unbiased estimation, maximum likelihood estimation; Neyman-Pearson theorem, uniformly most powerful tests, likelihood ratio tests, chi-square and F tests, nonparametric tests.

Wi Qtr. 5 cl. Prereq: 520. Not open to students with credit for 621.

528 Data Analysis I U G 3

Non-calculus treatment of descriptive statistics, statistical inference, goodness of fit, use of t, chi-square in one sample situation.

Su, Au, Wi Qtrs. 3 cl, lab hrs arr. Not open to students with more than 5 cr hrs in Stat. Not open to students who have completed Stat 145 or 245.

529 Data Analysis II U G 3

Two sample tests, non-parametric one and two sample procedures, regression analysis, one and two way analysis of variance.

Wi, Sp Qtrs. 3 cl, lab hrs arr. Prereq: 528 or equiv.

530 Data Analysis III U G 4

Multiple regression models; diagnostics, inferences, and variable selection; ANOVA with several factors, mixed models, nesting.

Sp Qtr. 3 cl. Prereq: 529 or permission of instructor.

574 Introduction to SAS Software U G 3

Inputting data, date manipulation and calculations, data presentation and reports, graphical displays, data and character data, formatting, macro programming, basic statistical procedures.

Au, Sp Qtr. 2 cl. Prereq: 529 or equiv or permission of instructor.

600 Statistical Consulting I U G 2

Role of statistical consultant; enhancement of problem solving and communication skills; development of a personal philosophy of consulting.

Au, Sp Qtrs. Prereq: 645 and permission of instructor. This course is graded S/U.

601 Statistical Consulting II U G 2

Experience is given the student in working with real data through association with projects in the Statistics Consulting Service.

Su, Wi Qtrs. 1 1.5-hr cl. Prereq: 600 and permission of instructor. This course is graded S/U.

602 Early Start in Statistics G 5

Selected mathematical topics, including geometric series, binomial expansion, integration by parts, Taylor series; transformation of variables, linear algebra, basic concepts of probability.

Su Qtr. 5 cl. Prereq: Grad standing in stat.

603 Teaching of Statistics G 5

Introduction to the teaching of statistics; teaching strategies; communicating with students; review of topics taught in Stat 133, 135, and 145, and the computing lab.

Su Qtr. 2 2.5-hr cl. Prereq: Grad standing in stat. This course is graded S/U.

610 Probability for Statistical Inference U G 5

Introduction to probability, random variables, and distribution theory intended primarily for students in MAS degree program.

Au, Wi Qtrs. 3 cl. Prereq: Math 548 or permission of instructor. Not open to students with credit for Math 530.

620 Statistical Theory I U G 4

Introduction to probability, conditional probability, independence, random variables, distribution functions, transformations, moment generating function, common probability distributions; marginal and conditional distributions, sampling distributions; convergence concepts.

Au Qtr. 4 cl. Prereq: Math 548. Not open to students with credit for 610.

621 Statistical Theory II U G 4

Sufficiency, maximum likelihood estimation, minimum variance, unbiased estimation, Bayes estimation, decision theory.

Wi Qtr. 4 cl. Prereq: 620 or written permission of instructor.

622 Statistical Theory III U G 4

Likelihood ratio tests, Neyman Pearson theorem and uniformly most powerful tests, confidence intervals, applications to linear models.

Sp Qtr. 4 cl. Prereq: 621.

623 Theory of Statistical Analysis U G 5

Estimation, hypothesis tests, best tests, likelihood ratio tests, confidence sets, sufficiency, efficient estimators; intended primarily for students in the MAS degree program.

Wi, Sp Qtrs. 3 cl. Prereq: 610 or 620 or permission of instructor. Not open to students with credit for 621 or 622.

625 Applied Bayesian Analysis G 4

Introduces various aspects of Bayesian modeling (including conditionally specified models and models for non-normal data) and simulation-based model-fitting strategies.

Wi Qtr. 2 2-hr cl. Prereq: Statistical Theory (Stat 520/521, or Stat 610/623, or Stat 621/622) and Applied Regression Analysis (Stat 645) or permission of instructor.

628 Statistical Practice I G 4

Computing environment; statistical computing; scientific method; overview of statistical problem formulation and inference; foundations of stochastic modeling; exploratory data analysis; descriptive statistics.

Su Qtr. 4 cl. Prereq or concur: 620.

632 Applied Stochastic Processes I U G 3

Conditioning, discrete time Markov chains, Poisson processes, branching process.

Wi Qtr. 3 cl. Prereq: 623 or permission of instructor.

635 Statistical Analysis of Time Series U G 3

Time series models; estimation of the spectral density function; transformations of time series; prediction theory applications.

Au Qtr. Prereq: 521 or 525 or 623 or permission of instructor.

641 Design and Analysis of Experiments U G 5

The linear model for experimental designs; analysis of variance; factorial experiments; and block designs.

Wi, Sp Qtrs. 3 cl. Prereq: 521, 645, and knowledge of elementary linear algebra; or permission of instructor.

645 Applied Regression Analysis U G 5

Simple and multiple linear regression, diagnostics, model selection, models with categorical variables.

Au, Wi, Sp Qtrs. 3 cl. Prereq: 521 or equiv.

651 Survey Sampling Methods G 4

Sampling from finite populations, simple random, stratified, systematic, and cluster sampling designs, ratio and regression estimates; non-sampling errors.

Wi Qtr. 2 2-hr cl. Prereq: 521 or permission of instructor. Not open to students with credit for PubH-Bio 651. Cross-listed in Public Health: Biometrics.

652 Applied Statistical Analysis with Missing Data G 4

Models and methods for the dataset with missing values, including imputation and likelihood and Bayesian-based models.

Au Qtr. Prereq: PH-BIO 703, STAT 529, or equivalent (or permission of the instructor). Knowledge of regression and familiarity with a statistical computing package are necessary.

656 Applied Multivariate Analysis U G 5

Matrix computation of summary statistics, geometry of sample data; multivariate normal distribution; MANOVA; principal components; discriminant analysis; topics may include factor analysis, cluster analysis, canonical correlation.

Wi, Sp Qtrs. 3 cl. Prereq: 645 or equiv and knowledge of linear algebra. Some experience with computers is expected.

661 Applied Nonparametric Statistics U G 5

Noncalculus treatment of nonparametric tests, confidence intervals, estimation; topics include one- and two-sample problems, one- and two-way analysis of variance, multiple comparisons, correlation.

Su, Sp Qtrs. 5 cl. Prereq: 521 or 529 or equiv.

662* Environmental Statistics U G 3

Environmental statistical methodologies applied to case studies; topics include the role of ecology, bioassay, risk, censoring, spatial statistics and hierarchical statistics.

Sp Qtr. 2 1.5-hr cl, 3 labs arr/qtr. Prereq: 530 or equiv.

663^ Statistical Methods in Reliability U G 5

Statistical failure models, graphical and analytic parametric estimation for censored samples, non-parametric survival function estimation, reliability of composite and repairable systems, Bayesian estimation and prediction.

Sp Qtr. 3 1.5-hr cl. Prereq: 521 or 623 or equiv.

664 Principles of Statistical Quality Control U G 5

Pareto diagrams; process control: Shewhart, CUSUM, empirical Bayes, multivariate and other control charts; economic design, process capability, Taguchi's method for off-line control; acceptance sampling.

Au Qtr. 3 cl. Prereq: 521 or 623 or equiv.

665 Discrete Data Analysis U G 4

Two-by-two tables; cross-sectional, prospective, and retrospective studies; log linear model analysis of cross-classified data; logistic regression analysis; analysis of stratified tables.

Sp Qtr. 2 cl. Prereq: 529 or 645 or permission of instructor.

673 Monte Carlo Techniques U G 3

This course covers the Monte Carlo topics of Stat 671.

Au Qtr. 3 cl. Prereq: 520 or 529 or equiv and some knowledge of computer programming, or permission of instructor. Not open to students with credit for 671.

674 Data Management and Presentation I U G 2

Inputting data, data manipulation and calculations, handling missing data, merging data, transporting data sets, dates and formatting, relational databases and structured query language; emphasizes use of statistical software SAS.

Au, Wi Qtrs. 1 2-hr cl. This course is graded S/U.

675 Data Management and Presentation II U G 2

Handling character data, custom reports, macro programming, graphics and multiple plots, output delivery system, transforming output to Web pages and other formats; emphasizes use of statistical software SAS.

Wi, Sp Qtrs. 1 2-hr cl. Prereq: 674 or permission of instructor. This course is graded S/U.

693 Individual Studies U G 1-5

Individual conferences, assigned readings, and repor ts on minor investigations.

Su, Au, Wi, Sp Qtrs. Prereq: Permission of instructor. Repeatable to a maximum of 20 cr hrs. This course is graded S/U.

694 Group Studies U G 2-5

Designed to give groups of students an opportunity to pursue special studies not otherwise offered.

Su, Au, Wi, Sp Qtrs. Repeatable to a maximum of 20 cr hrs.

722 Theory of Probability I G 4

Measure and integration; random variables; independence; convergence in probability, almost everywhere, and in the mean; conditional probability and expectation.

Au Qtr. 4 cl. Prereq: Math 653. Not open to students with credit for Math 722. Cross-listed in Mathematics.

723 Theory of Probability II G 4

Weak convergence; characteristic functions; central limit theorems; random walks; introduction to martingales.

Wi Qtr. 4 cl. Prereq: 722 or Math 722. Not open to students with credit for Math 723. Cross-listed in Mathematics.

742 Analysis of Variance G 3

Theory of the general linear model; least square estimates and properties, especially in non-full rank models; analysis of variance technique; factorial designs.

Au Qtr. 3 cl. Prereq: 521 or 623, and Math 471 or 601.

743 Generalized Linear Models G 3

Introduces the statistical theory and methodology to extend regresssion and analysis of variance to non-normal data.

Wi Qtr. 3 cl. Prereq: 645 and 742.

745* Multiple Comparisons Procedures G 3

Types and levels of multiple comparison inference, abuses, sample size computation, graphical representation.

Sp Qtr. 3 cl. Prereq: 742 or permission of instructor.

746 Design and Analysis of Experiments G 3

A continuation of 742; various experimental designs; analysis of covariance, mixed and random models.

Wi Qtr. 2 cl. Prereq: 742.

755^* Multivariate Analysis I G 3

Geometrical representations of data; random vectors, normal distribution for random vector and random data matrices, Wishart distribution, inferences based on normal theory.

Wi Qtr. 2 cl. Prereq: 521 or 623, and Math 471 or 601.

756^* Multivariate Analysis II G 3

Multivariate regression analysis; principal component analysis; factor analysis; canonical correlation analysis; discriminant analysis--all from a theoretical point of view.

Sp Qtr. 2 cl. Prereq: 755.

760 Elements of Statistical Learning G 3

Statistical and Machine Learning - Applied modern regression, pattern recognition and clustering techniques for discovery/understanding of underlying statistical structures within large, complex and noisy data sets.

Wi Qtr. 2 1.5-hr cl. Prereq: 610/623 or higher, or ECE 804/806; Familiarity with Matrix Algebra and Linear Regression Analysis. Final project report and class presentation is a key component of this course.

761* Nonparametric Statistics I G 3

Order statistics, equal in distribution technique, counting and ranking methods, distribution-free statistics, Monte Carlo power simulation studies, asymptotic relative efficiency.

Au Qtr. 3 cl. Prereq: 622 or 623.

763* Nonparametric Function Estimation G 3

Nonparametric function estimation with emphasis on smoothing splines, flexible model building based on noisy multivariate data, kernel methods, additional topics in smoothing.

Sp Qtr. 3 cl. Prereq: 622, 645, and knowledge of linear algebra.

764^* Order Statistics U G 4

Distribution theory in continuous and discrete cases, moments, order statistics in statistical inference, asymptotic theory.

Sp Qtr. 4 cl. Prereq: 622 or permission of instructor.

773 Statistical Computing G 3

Random number and variate generation, variance reduction, integral equations, resampling methods, maximization, E-M algorithm and other topics.

Au Qtr. 3 cl. Prereq: 622.

789 Survey Research Practicum G 5

Hands-on applications for students interested in the planning, implementation, and analysis of a scientific sample survey.

Sp Qtr. 1 3-hr cl. Prereq: Admission to grad interdisciplinary specialization in survey research and permission of instructor. Not open to students with credit for 789 in AED Econ, Agr Educ, Bus-Mktg, Econ, Edu P&L, Geog, J Com, Polit Sc, Psych, Pub Hlth, PubPol&M, or Sociol. Cross-listed in AED Econ, Agr Educ, Bus-Mktg, Econ, Ed P&L, Geog, J Com, Polit Sc, Psych, Pub Hlth, PubPol&M, and Sociol.

801 Seminar on Research Topics in Statistics G 2

Lectures on current research by each graduate faculty member in statistics.

Su Qtr. 1 2-hr cl. Prereq: 2nd yr standing in stat PhD program or permission of instructor. Repeatable to a maximum of 4 cr hrs. This course is graded S/U.

820 Statistical Inference I G 3

Statistical decision theory, foundations of statistics, Bayesian analysis, sequential analysis, sequential probability ratio test.

Au Qtr. 3 cl. Prereq: 622.

821 Statistical Inference II G 3

Sufficiency and invariance, unbiased and equivariant estimators, Neyman- Pearson, UMP, UMPU and invariate tests.

Wi Qtr. 3 cl. Prereq: 722, or Math 722 and 820.

822 Statistical Inference III G 3

Asymptotic theory for estimators and tests, resampling methods and other topics in modern inference.

Sp Qtr. 3 cl. Prereq: 723 or Math 723, and 821.

825* Advanced Bayesian Analysis G 3

Bayesian computation, nonparametric Bayes methods, semiparametric Bayes methods, robust Bayesian analysis, complex Bayesian models.

Wi Qtr. 3 cl. Prereq: 821.

829^* Spatial Statistics G 3

Spatial statistics at an advanced level; topics include geostatistics, lattice models with emphasis on Markov random fields, and spatial point processes.

Wi Qtr. 2 1.5-hr cl, 3 labs arr/qtr. Prereq: 622 and 645.

832 Applied Probability Models G 3

Birth and death processes, Queueing Theory, Branching processes and other applied probability models.

Wi Qtr. 3 cl. Prereq: Math 722.

833* Statistical Methods for Analyzing Genetic Data G 3

Basic principles of population genetics, linkage analysis, association study, genetic epidemiology, and analysis of gene expression data.

Au Qtr. 2 2-hr cl. Prereq: 622 or equiv or permission of instructor.

847^* Advanced Design of Experiments G 3

Partially balanced designs, factorial experiments, confounding and fractional replications, response surface designs.

Sp Qtr. Prereq: 746.

881 Advanced Topics in Mathematical Statistics I G 3

Topics to be taken from the following: multivariate analysis, stochastic processes, analysis of variance, components of variance models, advanced test design.

Su, Au, Wi, Sp Qtrs. 3 cl. Prereq: Grad standing in stat. Repeatable to a maximum of 9 cr hrs.

882 Advanced Topics in Mathematical Statistics II G 3

Continuation of 881.

Su, Au, Wi, Sp Qtrs. 3 cl. Prereq: Grad standing in stat. Repeatable to a maximum of 9 cr hrs.

888 Large Sample Theory G 3

Mann-Wald theory of stochastic order relationships; asymptotic distribution of maximum likelihood estimates and likelihood ratio statistic, large deviation theory, asymptotic theory of well-known statistics.

Sp Qtr. 3 cl. Prereq: 822.

891 Interdisciplinary Seminar

Graduate seminar for graduate interdisciplinary studies. Cross-listed in Biomedical Engineering, Biomedical Informatics, Biophysics, Computer Science and Engineering, Electrical and Computer Engineering, Integrated Biomedical Science, Pathology, Radiology, and Vision Science.

891.01 Interdisciplinary Seminar on Biomedical Images G 1-2

Graduate seminar for Graduate Interdisciplinary Specialization in Comprehensive Engineering and Science of Medical Images.

Au, Wi, Sp Qtrs. 1 cl. Prereq: Grad standing. Repeatable to a maximum of 3 cr hrs. This course is graded S/U.

893 Advanced Individual Studies G 1-5

Individual conferences, assigned readings, and reports on investigations.

Su, Au, Wi, Sp Qtrs. Prereq: Permission of instructor. Repeatable to a maximum of 20 cr hrs. This course is graded S/U.

894 Advanced Group Studies G 1-5

Designed to give groups of advanced students an opportunity to pursue special studies not otherwise offered.

Su, Au, Wi, Sp Qtrs. Prereq: Permission of instructor. Repeatable to a maximum of 20 cr hrs.

895 Statistics Seminar G 1

Topics range over the current research interests of statisticians from around the world; some lectures are of an expository nature.

Au, Wi, Sp Qtrs. 1 cl. Prereq: Permission of dept. Repeatable to a maximum of 10 cr hrs. This course is graded S/U.

999 Research G 1-18

Research for thesis or dissertation purposes only.

Su, Au, Wi, Sp Qtrs. Repeatable. This course is graded S/U.